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The power Internet of Things revolves around all aspects of the power system, and makes full use of mobile interconnection, artificial intelligence technology, and advanced communication technology to realize the interconnection of everything and human-computer interaction in all aspects of the power system. Build a smart service system with comprehensive status perception, efficient information processing, and convenient and flexible application. In this paper, aiming at the calculation and analysis requirements of collecting data on the edge computing node side, this paper studies the intelligent diagnosis algorithm on the edge computing node side based on ultrasonic sensors. Convolutional neural network is used to monitor the partial discharge of switchgear deployed on the edge side. Upload abnormal data to the platform layer for diagnosis and analysis, and promptly push early warning information to operation and maintenance personnel, and adjust status monitoring strategies.

This paper presents a hybrid technique of combining the BERT embedding method and the graph convolutional neural network. This combination is then employed to solve the text classification problem. Initially, we apply the BERT embedding method to the whole corpus in order to transform all the texts into numerical vectors. Then, the graph convolutional neural network will be applied to these numerical vectors to classify these texts into their appropriate classes. Especially, in our approach, we need only a few labeled texts for the model training. For the illustration, in this paper, we use the BBC news and the IMDB movie reviews datasets to perform our experiments, showing that the performance of the graph convolutional neural network model is better than the performances of the combination of the BERT embedding method with other classical machine learning models.

Every year, doctors diagnose skin cancer in around 3 million or more patients across the globe. Currently, it is one of the most widely recognized kinds of cancers for human health. Hence, we need an early diagnosis to prevail any critical condition of the infected patients. Apparently, it can treat with topical drugs, if it diagnoses in an early stage. Hence as an outcome, skin cancer is responsible for less than 1% of all cancer deaths. There are two types of tumors in the skin cancer diseases domain, such as benign and malignant. To develop a robust and early screening system to diagnose skin cancer, it requires an efficient algorithm for prediction, trained with a large dataset. The primary aim of this research is to develop an efficient skin cancer screening process using a robust deep neural network with a large dataset. In this paper, we intend to determine considerate and dangerous types of skin cancer tumors using dermoscopic images from a publicly available dataset. We proposed an efficient and fast scaled 2D-CNN based on EfficientNet-B7 deep neural architecture with image preprocessing. This paper also uses two different pre-trained deep neural architectures, such as VGG19, and ResNet-50 to compare the performance with the proposed architecture. The proposed architecture outperformed the other pre-trained CNN models whereas the proposed architecture achieved higher AUC and accuracy compared to other architectures.

This paper provides a mathematical model for the bladeless wind turbines working on vortex shedding principle. Unlike conventional wind turbines that work with rotary inputs, bladeless turbines require to generate power from vortex induced vibrations. Hence, it is required to have a mathematical model and equivalent circuit representation to help analyze the bladeless wind turbines and estimate different performance metrics. This may also be used in developing efficient control methodologies. A generalized mathematical model with three different equivalent circuit representations for the electro-mechanical system of a bladeless wind turbine is developed in this paper.

This paper focuses on physical faults and cyberattacks analysis and intelligent detection of faults/attacks with integrated fault-tolerant and cyber-resilient controllers for a PV system at microgrid level. The possibility of detecting and diagnosing faults/attacks rapidly enables the controllers to accommodate/mitigate the effects of faults/attacks in the microgrid system. This allows the microgrid to continue operation without any serious problems or interruptions. In this regard, the present paper considers a hybrid AC/DC microgrid composed of different renewable distributed generation resources. To monitor real-time data from the PV system at microgrid level, a hybrid intelligent diagnosis system with two parallel diagnosis units based on rule-based and model-based approaches, is presented. Lastly, the online information obtained from the diagnosis system is used by the controllers to guarantee safe operation of the microgrid during faults/attacks. The high effectiveness of the proposed strategy under different faults and cyber-attacks is demonstrated in an advanced microgrid benchmark model with wide variations in operating conditions and electrical loads.

Since 2020, hybrid learning has become the new convention of teaching and learning, whereby learning materials are delivered through a blend of synchronous and asynchronous sessions. In engineering education, this has led to the migration of laboratory teaching to the remote and virtual world. While immersive learning based virtual laboratory has been a great alternative for teaching hardware-based laboratory activities, this has however posed great challenge to software-based laboratory learning. Review of the literature on engineering education suggests an evident gap in pedogeological research to inform the application of blended laboratory learning. This paper thus presents a study case on the pedagogy of introducing blended learning adopted in the remote teaching of an electrical power engineering laboratory. The approaches integrated to facilitate the pedagogy and their implications are detailed in this work. Using Bloom’s taxonomy, the paper examines the role of blended learning in enhancing student learning experience in respect to learning autonomy and engagement.

AC microgrids are considered the most compatible method for integration of renewable energy sources and energy storage systems into the existing power grid. Photovoltaic (PV) systems are among the most popular renewable energy sources. However, due to the DC nature of their produced power, power electronics converters are required to process their harvested energy. This paper proposes a power electronics-based solution named solar converter unit (SCU) that operates as an interface between the PVs modules and the AC microgrid. The modularity of the proposed topology improves the reliability of power conversion process. Moreover, this topology benefits from a modified hysteresis band control algorithm that provides regulated and high-quality waveform at the consumer side with maximum of 6% error margin. Furthermore, a THD value of 0.72% is recorded for the consumer side. Various integration scenarios using SCU are discussed comprehensively in this paper and a scenario selection algorithm is proposed. Simulations are conducted for key functions of SCU to demonstrate its capabilities and functionality. The simulation results show that the proposed SCU converts and manages the power in the AC microgrid properly.

Railway vehicles have a lot of equipment, and their faults possibly have significant impacts on reliability and safety of railway operations. Some vehicles these days have Train Control and Monitoring System (TCMS), and constantly monitor and collect data of the equipment conditions during operations. In this paper, utilizing the monitoring data, we propose a method to continuously evaluate abnormalities of vehicle equipment using Neural Network with Long Short Term Memory (LSTM), which effectively and flexibly learn time series data. In the method, to realize anomaly detection, we introduce "anomaly score", which is an indicator to express the degree of abnormality of vehicle equipment. In this paper, we show that the anomaly score increases as a fault of an air-conditioning unit progresses from 1.5 month before its fault became apparent. Consequently, the reliability of the railway operation will be improved by evaluating abnormalities of vehicle air-conditioning unit or identifying signs of faults from monitoring data recorded with TCMS.

The upward trend of employing renewable energy sources in today’s power grid, the tendency to utilize energy storage systems in addition to these sources, and the benefits of using hybrid energy storage systems (including the transportation electrification sector) have put the multi-port converters (MPCs) under the spotlight. Fewer number of active and passive components, higher power density, and lower risk for cyber- attacks are among the reasons for MPCs’ popularity. This paper proposes a novel three-port power converter for the hybrid energy storage and hybrid renewable and energy storage applications. This converter is designed to operate for loads up to 20kW and for voltages 400-24V which is suitable for HESSs in residential and electric vehicle auxiliary power units. The voltage levels of this TPC are suitable for the electric vehicles auxiliary power units and DC zonal microgrids. This paper discusses the development and control of this three-port converter and demonstrates the effectiveness of this converter by simulating it under various operating modes for a 2.5kW hybrid energy storage system This TPC achieved efficiencies between 90.7% to 94.5% in different modes with a switching frequency of 50kHz.

DC microgrid can efficiently integrate the renewable energy sources, such as fuel cells and photovoltaic (PV) panels. However, due to the voltage mismatch between the low output voltage of renewable energy source and the high voltage of DC bus, a high voltage gain step-up converter interface between them is required. In this paper, a novel nonisolated DC/DC converter with high voltage gain is proposed. In addition to the high gain characteristic, the proposed converter provides ripple-free input current, which can prolong the service life of fuel cell and improve the generation efficiency of PV panels. Besides, lower voltage stresses of power switches and didoes contribute to enhancing converter efficiency. The operation principle, characteristics analysis and comparative study are also demonstrated in this paper. Finally, a 400W 40V/400V scaled-down experimental prototype is built to verify the converter performance and the theoretical analysis.

The induction machine is considered as the most reliable and robust electric machine and widely used for various applications. The induction machine is a nonlinear system. Therefore, its operating point stability analysis can be done using the Lyapunov function approach. In this paper, a model of the induction machine is analyzed, and an approach to find a Lyapunov function for the machine is discussed. The Lyapunov function has its region-of-attraction which is also analyzed in the paper. The simulation results are shown to support analysis.

This paper introduces an improved real-time Model Predictive Climate Control (MPCC) technique to reduce power consumption in Heating, Ventilation and Air Conditioning (HVAC) system of the Battery Electric Vehicles (BEVs). In the presented control technique, the fan, heating and cooling power usage is optimized considering the effect of the ambient temperature. Moreover, the need of a physical temperature measurement sensor is eliminated using an ambient temperature observer. In a typical BEV, the HVAC load is significant and it influences the overall vehicle performance and driving range. Therefore, a real-time control system capable of maintaining desired cabin temperature while achieving maximum HVAC efficiency is highly desirable. In the proposed MPCC, the optimum split of the battery power between the heating\cooling and the fan power is identified as a function of ambient temperature through an offline optimization process and used in the form of a lookup-table for real-time implementation. It is demonstrated that the proposed MPCC improves energy consumption efficiency of the entire HVAC system up to 5% by dynamically adapting to the variations in the ambient temperature. Furthermore, owing to the online temperature observation process, the proposed HVAC control system allows elimination of ambient temperature sensor and corresponding maintenance efforts. In this paper, the performance of the proposed MPCC is evaluated over a single-zone HVAC model of a BEV in MATLAB\Simulink® environment.

The power distribution grid is centrally managed concerning the requirements of the end-users, however, with the appearance of smart grids, new technologies arc arising. Therefore, distributed energy resources, mainly, renewables, energy storage systems, electric mobility, and power quality are viewed as encouraging contributions for improving power management. In these circumstances, this paper presents a power electronics perspective for the power distribution grid, considering innovative features, and including a power quality perception. Throughout the paper are presented relevant concepts for a concrete realization of a smart grid, supported by the integration of power electronics devices as the interface of the mentioned technologies. Aiming to support the innovative power electronics systems for interfacing the mentioned technologies in smart grids, a set of developed power electronics equipment was developed and, along with the paper, are shown and described, supporting the most important contributions of this paper., This work has been supported by FCT -Fundação para a Ciencia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. This work has been supported by the FCT Project newERA4GRIDs PTDC/EEI-EEE/30283/2017.

This paper proposes an unidirectional Boost Derived Hybrid Power Converters (UBDHC) which can drive both DC and AC loads from standalone Solar PV system and also it can be used to charge the batteries. Nowadays, most of the distribution systems have hybrid loads, i.e., both AC and DC loads. Since it is a solar PV based system so during day time we can drive both the AC and DC loads along with it charges the battery by using the solar PV power. The charged batteries can be used to drive the EV vehicles. This operation can be performed by using the single-stage power electronics converter called unidirectional boost derived hybrid converter (UBDHC). Modified unipolar sine-triangle PWM control technique is used to generate the control pulses to perform the inverter operation in the UBDHC. The shoot through state of the control pulses is used to drive the boost converter operation for DC output. In this paper the performance of the UBDHC has been evaluated for different combination of AC and DC loads, i.e., AC resistive/inductive, DC resistive and DC battery charging. The simulation studies of unidirectional boost derived hybrid converter are done through the MATLAB/SIMULINK software.

This paper introduces the time synchronization approaches to the Institute of Electrical and Electronics Engineers (IEEE) P1451.0 standard-based sensor networks for Internet of Things (IoT) applications. A time synchronization architecture of IEEE P1451.0 standard-based sensor networks is described including two-level time synchronization systems in IEEE P1451.0 and P1451.1.X standards-based wide-area network (WAN) and IEEE P1451.0 and P1451.5.X standards-based local area networks (LANs). However, this paper mainly focuses on the time synchronization approach of IEEE P1451.0 and P1451.1.6 standards-based WANs and provides two implementations of time synchronization of IEEE P1451.0 and P1451.1.6 using wireline and wireless networks with their preliminary results to verify that the time synchronization approach of IEEE P1451.1.6 functions properly. In addition, the time synchronization transducer electronic data sheets (TEDS) of P1451.1.6 is described.

In this paper, a loss-optimising branch energy control strategy is extended for the case of unbalanced grid faults. This proposed branch energy control strategy uses the circulating currents as degrees of freedom to control the energy of the module capacitors evenly between the branches. In order to generate the setpoints for the circulating currents, an enhanced analytical model of the modular multilevel converter is developed, considering grid asymmetries. Additionally, this paper explores the implementation and validation of the proposed control system in several fault cases. Both the simulation results and the experimental results of the low-voltage test bench show that the proposed control strategy operates reliably with little impact on branch losses.

The general aim of a cognitive Cyber Physical System of Systems (CPSoS) is to provide managed access to data in a smart fashion such that sensing and actuation capabilities are connected. Whilst there is significant funding and research devoted to this area, focus remains purely on creating bespoke systems. This paper presents a novel approach, based on a set of components to leverage Situational Awareness and Smart Actuation in large manufacturing industries with the focus on enabling predictive maintenance for asset and abnormal situation management. This paper presents a novel generic platform, named AtiCoS, that combines case-based and common-sense reasoning, as the enabling methodologies for enhancing CPSoS with cognitive capabilities.

The paper proposes a cognitive view on intonational contours aiming to describe their partitions in terms of elementary cognitive categories related to a generic information packaging (IPk) mechanism. We formulate the hypothesis that IPk structures pack auditory information items at the cortical level into relations that are marked at the utterance level by prosodic phrases. An IPk model based on this hypothesis is used in the paper for describing two pairs of contours that are presented in [1] as problematic for a categorical phonological description. The paper proposes a cognitive description of the respective contours after their partitioning into hierarchies of nested IPk units. In this view phonological events become marks of functional constituents at the cognitive level and the semantic differences between contours are reflected by their structural cognitive differences.

In three-dimensional reconstruction technology, it mainly includes the active time of flight method and the passive binocular stereo vision method. However, the time of flight method is easy to be affected by the external environment illumination and the corresponding device is expensive. The matching speed of the binocular stereo vision method is slow. Therefore, this paper chooses the line structured light method with good real-time performance, high accuracy and strong stability. The complex free-form surface is taken as the research object. Due to the serious mutual occlusion and high order derivability at any point, it is difficult to achieve complete 3D reconstruction on this surface. In this paper, a complete algorithm is designed for free-form surface reconstruction. Firstly, in order to solve the problem of beam discontinuity and sensitivity to strong light in the process of laser fringe center extraction, the gray gravity center method combining R-channel is proposed. Secondly, to solve the problems of the traditional optical plane calibration with few points and complex calibration process, a freely moving chessboard calibration method is proposed to improve the flexibility and accuracy of calibration. Then, the 3D point cloud is obtained and the surface is reconstructed using the measurement platform.

Wireless power transfer (WPT) is a well-known technique for electric vehicle (EV) charging. In this context, the power transfer profile is the key factor especially for the dynamic wireless power transfer (DWPT), where the time of magnetically coupling between track and pickup coils is significantly less. In this regard, this paper has proposed a three-element compensation network (3ECN) capable to transfer nominal power in the large portion of coupling, in other words, nominal power transfer is possible in the considerably large interval of mutual inductance. The paper has also included 1ECN and 2ECN and moved to 3ECN with a proper description of every CN and step-wise consideration and evolvement based on supply voltage limit, power transfer limit, and supply current limit. Simulation has been carried out in the MATLAB simulation environment considering the fundamental theory.

This paper presents a sensitivity analysis on the power to energy ratio for Energy Storage Systems (ESS) providing frequency response services on the Great Britain electricity network. Two services are considered; dynamic frequency response and dynamic containment, with the latter being a new service introduced in Oct 2020 by the Electricity System Operator. Each service proportionally responds in power to changes in grid frequency with each service differing in the response envelope. Whilst these services are based on power, for energy-limited assets such as ESS, the ratio of power to energy has an effect on its ability to deliver the service 100% of the time. In this paper, the availability, compliance against service terms and conditions, and equivalent cycles are considered showing that there is a significant difference between the two services. Currently, these services are delivered by battery ESS, however, it is demonstrated that the newer dynamic containment service can be effectively delivered by a higher power to energy ratio ESS and therefore offers opportunities for other technologies such as supercapacitors and flywheels.

The microgrids have been applied satisfactorily for the supply of energy to isolated places. In isolated microgrids, energy storage systems and dispatchable energy sources are fundamental for continuous operation, and for power balance. The dispatchable sources are useful as backup, for maintenance operations, and for battery bank equalization charges. Practical experiences in isolated microgrids that uses synchronous generator (driven by a prime mover) have a potential operation problem when working with rectifiers to charge the battery bank whenever the available renewable resources are not sufficient. This is due the generator reactance that causes voltage distortions at the generator terminals, power quality problems for the microgrid and, eventually, inhibition of rectifier operation whenever there is a thyristor switching. This paper proposes the design of a bidirectional DC-AC converter control loops for application in isolated microgrids, improving the power quality, efficiency and operation. In addition, the use of a bidirectional converter reduces energy conversion losses and reduces the costs of implementing the microgrid by replacing two pieces of equipment (AC-DC and DC-AC converters) for just a single one. The contributions of the paper are the design methodology of the control loops of a bidirectional converter, whose development and application in real environment allows it to perform as grid-forming converter in isolated microgrids.

This paper provides a detailed explanation of several approaches that can be used to conduct online labs for electronics/mechatronics engineering courses and explains the results obtained from a survey conducted. The detailed explanations provide information on how to implement the method, benefits of the stated process, possible challenges, and how to overcome those challenges. Furthermore, this paper presents the analyzed results from a survey conducted to capture the student experience in online labs.

For offshore wind power plant based on modular multilevel converter based high-voltage direct current (MMC-HVDC) transmission technology, when a short-circuit fault occurs on the onshore AC network, the DC-link voltage will rise rapidly, which may even cause equipment damage. The existing scheme basically is to connect a DC chopper in parallel on the DC bus to absorb the excess energy, but the additional equipment will increase the construction costs and land use. For this reason, this paper proposes the MMC topology with integrated energy dissipation resistors, which is capable of passing through AC short-circuit faults. This paper studies the electrical parameter design method and the corresponding control strategy of the topology, and verifies the feasibility of the scheme through simulation. Compared with the existing DC chopper solution, this scheme is relatively simple in control, and can reduce the fluctuation of the DC-link voltage, construction costs and land use due to its integration with MMC.

The power consumption in data centers continues increasing, thereby pushing the converter to achieve high efficiency and high power density. This paper presents an asymmetrical half-bridge flyback converter for data center applications. Compared with an active clamp flyback converter, it functions as an isolated buck converter, and is more preferable for voltage step-down applications. The operating principle and the design considerations are included in this paper. An interleaving winding layout with uniformed current distributions is used for the planar transformer design. The built prototype satisfies an industrial standard low-profile sixteenth brick requirement, and achieves 94.9% peak efficiency and 468W/inch3 power density.

This paper presents a detailed review on different architecture topologies for Electric Vehicle (EV) charging station. The proposed paper enables to have a solid reference on electric transportation charging station topologies on different levels starting from the infrastructure of common bus to types of chargers and power flow uni/bi-directionality. Besides, two detailed comparative analyses on recent proposed EV architecture topologies based multilevel converters as Cascaded H-Bridge (CHB) and Neutral Point Clamped (NPC) converters are elaborated. The presented CHB analysis tackles enhancements’ attempts on charging time, balancing batteries’ State-Of-Charge (SOC), reducing power losses and balancing capacitors’ voltages. However, the presented NPC analysis includes attempts in improving NPC’s limited voltage balance operation, balancing the bipolar DC bus, regulating load disturbances, enhancing power quality and power utilization. The two analyses are summarized in two comparison tables to sum up the aim and the enhancement of each presented attempt.

This paper presents a solar power generation prediction technique using artificial neural network. The predicted data is then applied to the adaptive power management strategy for Photovoltaic (PV) generation units in a standalone microgrid. The intermittent nature of solar power generation leads to major challenges in power system planning and load sharing. Prediction of solar power generation based on weather conditions and the proper use of this data in power management strategies improve the performance of existing standalone systems. This paper proposes an adaptive control strategy, which uses the predicted value of solar generation to determine the mode of operation. An ANN model is developed and trained using the dependency of solar power generation on weather parameters. The trained model is used to predict the expected solar power generation at any time. The applicability of the proposed adaptive control method is analyzed using Matlab/Simulink based simulation studies.

A photo-voltaic (PV) system based grid-connected current source inverter has been investigated in this paper. In this paper, a photovoltaic (PV) system based grid-connected current source inverter has been investigated. For obtaining the maximum power from the PV system, we have developed a Lyapunov energy function-based control scheme. Operation of the system under unbalanced grid voltage condition has been reported and a methodology to extract maximum power from the PV system is articulated. In addition, to achieve optimal performance of the Lyapunov energy function based power controller, an existing parameter update scheme is employed and an optimal performance of the overall system is achieved. Detailed analysis of the proposed power controller with the feature to operate successfully under unbalanced grid voltage condition has been substantiated and discussed along with the effect of parameter update on the overall control architecture. The proposed system is verified via software simulations in MATLAB/Simulink and PLECS domain and various case study results are presented which corroborate the efficacy of the proposed framework.

The robot needs to know the pose in order to maintain stability and execute the walking path. Current solutions either rely on visual data, which is easily affected by the environment and lighting conditions, or integrate kinematics and inertial measurement unit (IMU) measurement data, however, there will be drift problems caused by accumulated errors. Aiming at the defects and stability problems of vision sensor in location, this paper combines vision sensor and IMU to complete the high-precision pose estimation at low cost, designs the combined positioning algorithm based on the extended Kalman Filter (EKF). Specifically, this paper proposes the number of correctly matched feature points and depth error as the judgment conditions of the combined strategy, and uses the IMU data to construct a process model, merges the pose estimation results of the vision sensor, and selectively corrects the vision sensor. The robot positioning experiment was carried out in the indoor laboratory scene, results show that the algorithm proposed in this paper can effectively suppress the positioning stability problem of the vision sensor and improve the accuracy of the pose estimation.

This paper aims to optimize the energy cost for Hybrid Thermal Electric Vehicle (HTEV). The considered HTEV combines an irreversible source fuel tank with two electrical sources, namely a lithium-ion battery and a supercapacitor. The complementarity of these energy sources improves the overall performance of the traction system. More precisely, the main objective of this article is to minimize the cost of the vehicle's mission, by exploiting the on-board energy mix. To establish a compromise between the simplicity of the real time implementation and the optimality of the solution, this paper develops a strategy that combines an optimization technique with a deterministic method. The proposed approach consists firstly in distributing the traction power between the thermal engine and the electric motor. This sharing is treated as an optimization problem under constraints. The corresponding objective function includes the on-board sources operating costs as well as penalty cost on CO2 emissions. This problem is solved using the Bellman algorithm through the dynamic programming. Thereafter, the adopted energy for supplying the electric motor is shared between the battery and the supercapacitor using a deterministic rule, namely frequency separation. To achieve optimum performances from on-board electrical sources, ajudicious choice of the sharing filter cut-off frequency is made based on several criteria, namely: the effective power, the state of charge variation, and the storage devices charge and discharge cycle number. The effectiveness of the proposed energy management system is illustrated with various simulations carried out under the Matlab environment.

This paper aims to highlight the methods of predicting the future behavior of a system's health and the remaining useful life to determine an appropriate maintenance schedule. Indeed, prognostic and health management techniques dedicated to renewable energy systems with special reference to wind turbine generators and papers published in the last ten years, are presented. Therefore some applications of prognostics in renewable energy systems, including power converter devices, batteries capacity degradation, and damage in wind turbines' high-speed shaft bearings, are highlighted.

In this paper, harmonic stability of a back-to-back modular multilevel converter based voltage source converter high voltage direct current system is analyzed. These systems are prone to ac- and dc-side resonances and interactions between the converter and its interconnected systems. The stability of the system can be predicted by the impedance based stability criterion, which requires the modeled or measured converter impedance. The analysis in this paper focuses on interoperability when the converters employ different control schemes in order to utilize the inherent damping properties of the sum capacitor voltage balancing control loops.

This paper discusses the start-up process for a dynamic wireless power transfer system to an electric vehicle passing a road-side coil. To transfer maximum energy in a short time, the process of detecting an approaching vehicle and transmitting power must be carried out quickly. In most of the previous studies, problems of vehicle detection and power transmission have been considered separately. In this paper, the power transmission control process is proposed that combines vehicle detection and current control. The detection process uses only vehicle-side voltage pulse which enables both road-side and vehicle-side coils to sense approaching of the vehicle-side coil. And the current control suppresses the current overshoot at the start of power transmission. The proposed method was verified by experiments. Both coils could detect another one at a sufficient distance from each other. Additionally, power transmission starts at a point of small coupling coefficient was achieved without current overshoot.

For the coils design of the inductive power transfer (IPT) system, the coils for the received-side and the transmitter-side are usually designed symmetrical in order to obtain better coupling coefficient and for simplicity. Along with a growing number of space-constrained devices, such as drones and small automated guided vehicles (AGV), much more flexible designs of receiver coil, such as asymmetrical coil designs are of great interest. Nevertheless, since power transfer efficiency of the IPT system is highly correlated with the parameters of coils, it is challenging to convert symmetrical coils into asymmetrical coils while maintaining the power transfer efficiency and the load independent output. This paper proposes a design methodology of converting symmetrical coils into asymmetrical coils for series-series inductive power transfer (SSIPT) that keeps similar transfer efficiency and maintain the load independent current (LIC) output. The analysis of coils’ parameters including the size and transfer distance is also taken into consideration, and the asymmetrical coil design flowchart is also introduced in this paper. Finally, a 30W experimental platform of the SSIPT system is built, and the experimental results verify the theoretical analysis and the practical feasibility of the proposed asymmetrical coil design.

DC miniature circuit breakers (MCB’s) are being used widely in low voltage dc (LVDC) grids for protection of dc systems against short circuit and over current faults. DC-MCB interrupts the fault when the fault current reaches the preset value. MCBs take a longer time for the fault interruption due to the mechanical inertia between the breaker contacts and also due to high dc currents, which may create protection issues in highly critical systems. Hence, improvements in the performance of existing DC-MCB is proposed by connecting a parallel power semiconductor branch to it. In the proposed configuration, only a power device and its control circuit is added which helps in faster commutation and transfer of current. Proposed concept also improves reliability of the DC-MCB as there is no arcing in the fault interruption process. This paper presents the experimental validation of the proposed concept in a dc system with a nominal rating of 100VDC/6A. Paper also elucidates the performance comparison of both the proposed concept and the DC-MCB.

This paper presents the implementation of industry grade renewable energy source phasor time-domain models from the Western Electricity Coordinating Council (WECC) Renewable Energy Modeling Task Force (REMTF) utilizing the OpenIPSL Modelica library. The modules described in this paper are generic, thus being able to be used to represent photovoltaic (PV), battery (BESS), and wind energy sources in transient stability scenarios, with added modularity given the object-oriented nature of Modelica models. The modeled components are briefly described, giving emphasis on how they were modeled in Modelica and coupled to the OpenIPSL library. Finally, the models described in this work were validated against the commercial software tool Siemens PTI PSS®E and showed to accurately replicate its results bringing validity to the Modelica-based implementation.

This paper presents a new modular magnetic structure for high-power wireless Electric Vehicle (EV) charging. To increase the output power level and reduce the implementation costs, a modular multi-receiver magnetic structure is proposed. In this method, the receiver coils are placed in a specific spacing from each other to have zero mutual inductance between them. Therefore, the maximum transferable power will be increased and the circuits will operate independently. Moreover, a modular structure will reduce implementation costs. In this paper, a two-receiver coil and a three-receiver coil system are designed and the decoupling method is explained in detail. The resonant compensation networks are select for each system to supply 11 kW with a single receiver, 22 kW with a two-receiver coil and a 33 kW with a three-receiver coil system. The performance of these systems is analyzed and simulation results are presented to validate the feasibility of the system.

A wireless sensor network (WSN) depends on energy to operate and considerable efforts have been devoted to extend its operational lifetime. Energy harvesting (EH) has emerged as one promising approach to prolong the lifetime of a WSN without interrupting its operations. In an EH-WSN, sensor nodes typically have batteries being charged with energy harvested from ambient environments such as wind, solar, water mills etc. However, uncertainties remain about when and how much energy can be harvested over time from the environments and about traffic fluctuation at each node. Unfortunately, existing works on EH-WSN are limited in evaluating the impacts of these factors and the number of the nodes in an EH-WSN on its key performance metrics. This paper, therefore, presents a general method and a practical implementation of a node capable of harvesting solar energy in an EH-WSN. The paper then evaluates the performance of the EH-WSN. Explicit mathematical expressions define models for network operational time, throughput and reliability of the EH-WSN and simulations are used to validate the models. Influential factors are energy arrival rate, traffic rate at each node and the number of nodes in an EH-WSN. The results document that the analytical models and simulations correspond.

Light Emitting Diodes (LEDs) have become pervasive in modern lighting and automotive applications. LED drivers regulate LED current which sets their luminous output, where dimming is an important attribute. Dimming techniques fall in one of two categories: "analog" or "duty-cycled" (pulse-width-modulated), and duty-cycled (PWM) dimming decomposes into three further classes: shutdown, shunt- and series-switched. However, a comprehensive analysis of dimming techniques, corresponding power losses, and their dimming capabilities is lacking in the literature. This paper explains and quantifies those in the context of a switched inductor (SL) DC–DC converter. Presented analysis incorporates SL conversion efficiency and models luminous flux, dimming range, and luminous efficiency. This paper reveals and verifies that analog dimming is up to 57% more efficient with the widest dimming range.

Mobile phones are becoming a common tool for people to make the payments. The current peer-to-peer mobile based payment system allows two parties to use physical location-limited interaction between their devices to facilitate secure payment. This physical location-limited interaction is ensured by enabling wireless proximity through Near Field Communication (NFC) technology embedded in mobile phones. However, the NFC technology is vulnerable to relay attacks which is a very challenging security problem. This paper proposes a novel new proximity channel based on vibration for peer-to-peer mobile payment system. The built-in vibrator and accelerometer on the phone are used to send and receive the information. The communication ensures the payment is conducted at a close distance. This paper also compares and analyse the method with the other method such as the phone vibration data and encrypt One Time Password (OTP) as the vibration pattern for payment. The result shows that the proposed method is able retrieve the information successfully from the other smartphones and guarantees the transaction is safe from relay attacks and eavesdropping.

This paper presents an implementation methodology to model a single delta bridge cell (full-bridge) modular multilevel converter static synchronous compensator (SDBC-MMC-STATCOM) in FPGA based real-time simulator. Mathematical modeling of full-bridge submodule and equivalent circuit-based modeling of single delta bridge cell modular multilevel converter is presented. This paper also discusses about different discretization strategies to convert continuous time equations into z-domain equations for implementation in field programmable gate array (FPGA). The discretized equations are verified by comparing its voltage and current waveforms with its equivalent model developed using the Simscape Electrical Specialized Power Systems library in Simulink. The testing is carried out with 4kV, 2MVA STATCOM model with phase-shifted carrier-based modulation. The model is then implemented in FPGA to perform real-time simulation in OPAL-RT real -time simulator. The tests verify that the real-time model of the STATCOM behaves similar to the Simulink reference model for positive sequence reactive power compensation with no voltage unbalance at the point of common coupling (PCC).

This paper presents a method of wide angle fovea visual odometry (WAF-VO) for Wide Angle Fovea Sensor SLAM (WAF-SLAM), by which a unique locally-high accurate and wide-angle map is generated in addition to camera motion estimation. The WAF sensor is a special-made wide-angle sensor that is inspired from human visual function, i.e., the spatial resolution of the image is not uniform throughout the entire field of view (FOV); it is much higher in the central FOV and decreases rapidly towards the periphery. Our visual odometry method is strongly characterized by a wide-angle FOV and space-variant resolution of the input image from the WAF sensor. A locally-high accurate and wide-angle mapping method is proposed as a major part for WAF-SLAM together with the camera motion estimation. Our proposed method estimates camera motions more stably using very low-spatial-resolution wide-angle images remapped from the input image of the WAF sensor. Using the estimated camera motions, narrow-angle high accurate maps are generated from corresponding feature points in high-spatial resolution central regions of the input image. Wide-angle maps are generated from ones in middle-spatial-resolution wide-angle images remapped from the input image apart from the above very low-spatial-resolution images. When the wide-angle maps are generated, the number of extracted feature points is increased by adjusting contrast threshold values of SIFT feature according to regions of the FOV. A KNN matching method improved using epipolar constraint is proposed and employed for avoidance of mismatching the increased feature points. Thus, the wide-angle maps are generated from more correct corresponding feature points. Finally, the above two types of maps are combined into the unique locally-high accurate and wide-angle map, i.e., a WAF map. Using our proposed method, the WAF map was generated by verification experiments. Furthermore, the paper presents an evaluation of the accuracy and precision of the generated map.

This paper presents an enhanced three-phase shunt active power filter (SAPF) that, besides its inherent functionalities of power quality problems compensation, also allows the interface of a renewable energy source (RES, namely solar photovoltaic – PV panels) and an energy storage system (ESS, namely batteries) through its dc-link. On the power grid-side, a three-phase four-wire voltage-source ac-dc converter is connected with the power grid, operating as an SAPF, whereas the RES-interface and the ESS-interface are made through a three-port multilevel dc-dc converter connected to the dc-link of the SAPF. Besides, to compensate power quality problems related to currents, the SAPF also permits the controllability of the bidirectional power exchanged between the power grid and the dc interfaces, i.e., the RES and the ESS. The operation principle of the whole system, as well as the detailed control algorithms, are described in the paper. A validation was performed through computer simulations, where it is possible to analyze the different operation modes of the enhanced SAPF interfacing a RES and an ESS through the dc-link.

This paper presents a design, simulation and development of rectangular tapered dielectric rod antenna fabricated using 3D printing technology. The focused impedance bandwidth of the antenna's operating frequency range sits on Ku band, which is between 12 GHz and 18 GHz. The resonant frequency was set at 13 GHz. Signal excitation of the rod antenna is through a WR62 waveguide, specific for the Ku band frequency. The reflection coefficient, maximum gain and efficiency are the main performance metric of the antenna development. The antenna simulation achieved a maximum gain of 13.10 dB, and efficiency of 98.83%. Detailed analysis of the antenna's tapered feed is presented in the paper. The antenna was fabricated using fused deposition modelling technique with 4 types of dielectric materials namely COC, ABS, PLA and PeTG.

Protection of DC distribution systems poses a significant challenge due to the absence of reliable and fast protection devices that can cater to the protection requirements of DC networks. This paper proposes a modular hybrid circuit breaker (HCB) architecture for DC distribution systems. Based on the idea of voltage and current sharing between cascade and parallel connection, it uses HCBs with low voltage and current capability to apply on higher voltage and current applications. The proposed scheme features high reliability, high flexibility, and a low-cost design. In this paper, the design procedures including voltage and current balancing techniques used are presented in detail. The effectiveness of the proposed architecture is successfully verified in a 5kW experimental setup. All the experimental results show a good agreement with the theoretical knowledge.

The hybrid-series-converter-(HSC) has enhanced operating modulation-index-(MI) range as compared to the parallel-hybrid-converter-(PHC). However, the HSC is underutilized when employed for high-voltage-direct-current-(HVDC) applications, HSC-HVDC. The parallel-chain-links-(PCLs) of HSC-HVDC generate fixed voltage and the series-chain-links(SCLs) of HSC-HVDC serves only as voltage wave-shaping circuit and does not increasing the output voltage levels. Thus, energy storage requirement of HSC-HVDC is higher than PHC. The switches of HSC-HVDC undergo forced commutation and increase losses. This paper intends to extract all the advantages inherent with the HSC and utilize it to its maximum capability by operating it as a static-compensator-(STATCOM), HSCSTATCOM. The proposed HSC-STATCOM requires lesser switching devices, capacitors besides having reduced energy storage requirements and zero-voltage-switching-(ZVS) nature. A new capacitor voltage control technique during unbalanced grid conditions is also proposed in this paper. The operating principle of the proposed STATCOM and proposed control technique is validated using different simulation case studies.

The flow of DC in AC networks leads to half-cycle saturation of power transformers that causes their internal heating, large draw of reactive power and ultimate grid collapse. Transformerless power electronics-based module integrated between the neutral and substation ground of traditional transformers has previously been proposed that provides power system protection against DC flow in grid along with a variety of advanced grid-support features. The technique has already been tested and verified on a controller hardware-in-the-loop (C-HIL) platform. In this paper, the proposed strategy is evaluated on a laboratory scale hardware prototype utilizing Typhoon power hardware-in-the-loop (P-HIL) strategy. The experimental results verify the promising performance of the proposed scheme in nullifying the effect of DC injection, performing harmonics isolation and voltage regulation. Also, an effective transformer and converter protection scheme utilizing a hybrid AC/DC solid-state switch has been proposed and evaluated in this paper.

This paper introduces a new circuit topology of power semiconductor switching devices for a high efficiency and cost-effective solid-state switch, especially for motor control applications. The proposed topology involves the combination of Thyristors (SCR) and Field Effect Transistors (FET) in a parallel arrangement. This new configuration permits the maximization of efficiency and enables higher power density through the minimization of the heat load compared to state-of the-art solutions. Whereas power loss during nominal current operation are minimized by the conduction characteristic of Field Effect Transistors, power loss during high current conditions (e.g. occurring during magnetizing inrush currents and motor start overcurrent) are minimized by the conduction characteristic of Thyristors. In this paper, we describe this novel circuit topology and the control circuit, and we validate the performance of the topology through full power experimental validation for a 480 V, 7.5 Hp induction motor in both continuous 12A operation and 8-time rated current of overcurrent capability tests.

This paper presents design considerations and experimental verification of a GaN-based half-bridge 650V/160A power converter block with four parallel 650V/60AGaN High Electron Mobility Transistors (HEMTs) for high-power traction drive applications. Paralleling of semiconductor devices is common for high power density applications. However, paralleling more than two GaN devices is challenging as parasitic inductances and resistances need to be well matched for all the devices. In addition, the DC loop inductances must be minimized to reduce the device voltage overshoot during turn-off. The gate loop inductances must also be matched and minimized to improve current sharing and reduce gate voltage oscillations. A detailed design method of a half-bridge with four parallel devices is discussed in this paper for matching gate and DC loop inductances. A half-bridge test circuit with four parallel enhancement-mode GaN (e-GaN) HEMTs is designed following the design method. The inductance matchings are verified with a detailed Q3D simulation. Finally, Double Pulse Test (DPT) results at 400V/160A are presented in this paper to demonstrate the half-bridge converter block’s current sharing and loss distributions.

This paper investigates the dynamic characteristics of AC microgrids in the presence of Constant Power Loads or Constant Power Sources (CPL/CPS). This dynamic characteristic is useful for understanding how AC microgrids behave in different operating points. If the dynamic characteristic is not desired, microgrids’ components can be tuned or proper approaches can be adopted to improve it. In this paper, the input impedances of a non-ideal CPL/CPS is mathematically derived through vigorous modeling. Moreover, the closed-loop output impedance of a distributed energy resource regulating the microgrid voltage is modelled. A unifying approach is adopted to transfer impedances of AC microgrid components to the same coordinate in order to utilize impedance-based stability analysis to assess the dynamic characteristics of AC microgrids in different operating points. Finally, simulation results are provided to validate findings.